CRSYSep 11, 2019

Privacy-Aware Cost-Effective Scheduling Considering Non-Schedulable Appliances in Smart Home

arXiv:1909.05300v11 citations
Originality Incremental advance
AI Analysis

This addresses privacy and cost concerns for smart home users, but it is incremental as it builds on existing scheduling methods by incorporating non-schedulable appliances.

The paper tackled the problem of scheduling smart home appliances to reduce electricity costs while protecting user privacy from smart meter data, achieving effective scheduling that meets privacy requirements as demonstrated with real-world data.

A Smart Home provides integrating and electronic information services to help residential users manage their energy usage and bill cost but also exposes users to significant privacy risks due to fine-grained information collected by smart meters. Taking account of users' privacy concerns, this paper focuses on cost-effective runtime scheduling designed for schedulable and non-schedulable appliances. To alleviate the influence of operation uncertainties introduced by non-schedulable appliances, we formulate the problem by minimizing the expected sum of electricity cost under the worst privacy situation. Inventing the iterative alternative algorithm, we effectively schedule the appliances and rechargeable battery in a cost-effective way while satisfying users' privacy requirement. Experimental evaluation based on real-world data demonstrates the effectiveness of the proposed algorithm.

Foundations

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